Retail Management Research Articles

Continuous increasing consumer service for multi-item dual-channel retail management

Along with the advancement of technology and consumer expectations, online-to-offline retailing is seeking attention in the retailing industries. Online-to-offline retailing is a powerful strategy that bridges the gap between the convenience and reach of online shopping with the tangible experience and service of physical stores. Customer satisfaction and brand loyalty are basic pillars to enhance profit for the retail industry. Providing different services like repairs, exchanges, and home delivery enhances customer satisfaction and builds trust in the particular industry. In e-commerce, the importance of delivery service is emphasized, with fast and reliable delivery being a key factor in customer satisfaction. An online-to-offline retailing system for multiple items is developed in this study by considering consumer service efficiency demand. A pricing strategy that relies on the channel of distribution and the impact of advertising on consumer demand is taken into account. The manufacturer offers complimentary home delivery services for orders surpassing a specified threshold. To implement advanced technologies, a huge budget is required. To make the study realistic, a budget and space are considered. The retailing system's total profit is ultimately maximized by determining the optimal values for selling price, advertisement investment, customer care costs across various channels, ordering quantity, and investment to minimize setup costs for different items. A classical optimization approach is employed to derive a semi closed-form solution for the proposed model. Sensitivity analysis and examination of special cases are provided to demonstrate the practicality of this research. Through numerical illustrations, it is established that the profit maximization occurs when the defective rate adheres to a Chi-square distribution. Imposing budget and space restrictions leads to a 19.91% increase in system profit while offering free home delivery services boosts the profit by 15.77%.

Role of Retail Management with Reference to Max Fashion Company

Role of Retail Management with Reference to Max Fashion Company

Pricing strategy based on a stochastic problem with barter exchange under variable promotional effort for a retail channel

Barter exchange platform gains popularity as an effective trade exchange strategy to minimize the vast use of paper money. In retail management, the application of the barter platform is growing because of cashless trade. It allows a retail enterprise to trade unused products in exchange for other assets purchased by reducing the actual purchase of assets. In this context, the study analyzes a stochastic model of a barter exchange problem under a retail channel. It investigates the barter exchange policy in three different models: conventional newsvendor model without barter exchange, with barter exchange, and with barter exchange with promotional effort and emissions level. The market demand for products is considered random and random with deterministic variables for three types of models. Stochastic models are solved in two different ways: with and without probability distribution functions of the random market demand. For maximization of the retailer's profit, the proposed framework obtains optimal decisions on ordered quantity, retail price, promotional effort, and emissions level. Five examples are tested and numerical results show that the barter exchange policy is more profitable than a traditional newsvendor model. A combination of stochastic and deterministic variable demand provides 34.31% more profit than a stochastic demand. Sensitivity analysis, discussions, and managerial insights are provided in detail on optimal decisions.

Bortom servicefronten. E-handelsarbetets platser och ojämlikhetsmönster

The digitalization of retailing is restructuring consumption as well as retail work. Unlike front-line service work in stores, online retail work is defined by indirect service work at a distance from customers at warehouse sites. The rapid pace of change means that knowledge about online retail workplaces and its employees is still fragmentary. Empirically drawing on Swedish national statistics and an ongoing study of five online retail warehouses, this article explores intersections of online retail warehousing, gender and racialization, and meanings of place therein. National statistics show that online retail employs more men and more foreign-born than retailing in general. While retailing is dominated by small workplaces, online retail warehouses are either small or large and the proportion of women and Swedish-born is lower at the larger warehouses than the small ones. Occupational data show that the proportion of women and foreign-born people is significantly lower among online retail managers than among warehouse workers. Further nuances are provided by the qualitative insights from the five studied warehouses. Almost only women worked in the two smaller warehouses, which was explained by references to the nature of the work. At the larger, more gender-balanced warehouses, examples of segregation between employees of the same category were found, as was the importance of place for hierarchies between workers and managers. More so, the study makes evident that place matters also for the boundary making around and between online retail workplaces, especially in relation to racialization processes. While inequality, place and work in retail stores are about conditional access to employment, in online retail warehouses the matter seems to be more about how certain bodies’ lack of mobility and opportunities in the labor market at large left them “stuck” in online retailing.

Money at my Fingertips: Decoding the Role of Referent Network Size and Financial Knowledge in Reinforcing Continuance Intention of m-Payment Services

ABSTRACT Service providers are ardent about promoting mobile payment (M-payment) technologies that enhance customer experience and foster a favorable attitude toward M-payments. Considering this, our study investigates the continuance intention of M-payment services, encouraging mobile users to utilize M-payments in their everyday financial transactions. Our research used structural equation modeling (SEM) to expand the horizons of the unified theory of acceptance and use of technology 2 (UTAUT2) and the traditional behavioral intention model (TBIM) in M-payments. The survey examined the intention of 620 mobile users to continue using M-payment services. Mediation and moderation techniques explored the models’ direct and indirect relationships. The results show that users’ attitude toward M-payment is amplified by quality of service, financial knowledge, perceived enjoyment, and referent network size, further escalating the continuance intention of M-payment services. Customers’ attitudes toward M-payment services partially mediate the relationship between the underlying constructs. Moreover, perceived customer responsiveness strengthens the link, whereas perceived technological uncertainty weakens the association between user attitude toward M-payment services and continuous intention. The study results could be useful for various stakeholders, including M-payment service providers, retail managers, customers, marketing companies, and policymakers, in enhancing India’s digital payment infrastructure.

Implementasi Strategi Manajemen Retail Setelah Pandemi di Lotte Mart Centre Point

The COVID-19 pandemic has had a significant impact on the economy and consumer behavior in Indonesia. In the midst of this situation, Lotte Mart Centre Point, as a retail store, faces a major challenge to survive and adapt to the changes. To address this challenge, a community service team from Universitas Battuta has implemented a retail management strategy using the Marketing Mix approach (Product, Price, Place, Promotion, people, process, physical evidence). This research aims to provide training, mentoring, and guidance to Lotte Mart Centre Point partners in implementing effective marketing strategies. Through training and mentoring activities, there has been a significant improvement in the enthusiasm and communication skills of partner employees. Evaluation shows that understanding and implementation of the Marketing Mix marketing strategy have also shown positive improvements. It is hoped that the results of this community service activity will help improve the economic performance of partners and strengthen their position amidst increasingly competitive markets. The conclusion of this study is that understanding and implementing the Marketing Mix marketing strategy is key to success in addressing economic challenges and changes in consumer behavior.

Pengaruh Hedonic Shopping Motives, Sales Promotion, Fashion Involvement terhadap Impulse Buying Shopee

Purpose: Consumer impulse buying has received considerable attention in consumer research. This phenomenon is interesting because it is not only driven by various internal psychological factors but also influenced by external stimuli related to the market. This study aims to determine whether there is an influence between Hedonic Shopping Motives, Sales Promotion, and Fashion Involvement on Impulse Buying of a Pradita University student class of 2020 – 2023 Business Management Study Program, Retail Management, and Accounting, who use Shopee e-commerce. Method: A quantitative survey method was used. The sampling technique used the nonprobability sampling method and purposive sampling, with a total sample of 140 people. Data collection techniques using online questionnaires. Primary and secondary data were used in this study. The analytical tool used in this study was multiple regression using SPSS 26. Results: The results of this research show that Sales Promotion and Fashion Involvement have no effect on impulse buying on the Shopee application, while Hedonic Shopping Motives have a significant positive effect on Impulse Buying among the Pradita University student class 2020 – 2023 Business Management, Retail Management, and Accounting Study Programs that use Shopee e-commerce. Limitation: The limited scope of research focuses only on Pradita University students from 2020 to 2023. Contribution: Fashion involvement has no influence on impulse buying among Pradita University students’ class 2020 – 2023 Business Management, Retail Management, and Accounting Study Programs that use the Shopee application.

Retailers' Response to Digital Transformation in the Industry: A Manager's Perspective

Prior to the COVID-19 pandemic, work disruptions were primarily linked to emerging technologies and expanding trade relations. However, the pandemic has highlighted the significance of the physical aspect of work. This study examines the effects of the growing prevalence of e-commerce in the retail sector by gathering insights from 20 retail managers. The participants were asked to provide their perspectives on the industry's transformation driven by digital advancements. The content analysis shows that the retail industry is changing rapidly and requires a deeper understanding of its driving forces. To keep up with the industry's digital power, future workforce management must implement appropriate strategies. One such strategy is transitioning to the future of work, which requires retail workers to acquire new skills to keep up with technological changes. To remain competitive, retailers must re-examine the in-store shopping experience. Strategic decisions should be made to optimize the workforce and focus on smarter operations. Effective inventory management can be a key differentiator for stores in a competitive market. With the right information, managers can make more informed business decisions. Digitizing the workforce can enhance employee engagement and productivity, resulting in cost savings that can be redirected to improving the customer experience. Further research is required to generalize the findings of this study. This can assist retailers in planning their business to achieve operational efficiency while remaining competitive.

How AI Enhances Retail Experiences?

Artificial intelligence (AI) is a powerful tool that can significantly enhance customer service and build customer trust, particularly for companies seeking to maintain a competitive edge in the retail business landscape. This study employs a thematic approach to investigate how automating the shopping experience with AI can enhance the retail customer experience. The study utilized random sampling techniques and interviewed 350 respondents at the shopping centre. Thematic content analysis was used to analyse the data. This method identifies interesting themes or patterns in the data and uses them to address research questions. It goes beyond simple data summarisation and involves interpreting and understanding the data. The results indicate that AI enhances the retail experience in various areas, such as customer service, product descriptions, marketing efforts, training, and interactive audio. Face-to-face interviews with retail managers revealed that four themes emerged from the discussion. Further research is required to generalise the findings of this study. This will undoubtedly assist retailers in planning their business to achieve operational efficiency while remaining competitive in the era of AI.

Optimizing retail prosperity: Strategic working capital management and its impact on the global economy

This study explores the critical role of the retail sector in the global economy and the importance of working capital management within retail businesses. Recognizing retail’s influence beyond just income generation, the research examines its impact on economic stability, job creation, and national GDP, and how it links industries such as manufacturing and logistics. Employing a blended-methods approach, the study integrates quantitative analysis using AMOS software with qualitative insights from interviews with financial managers and retail experts. Key focus areas include cash flow management, market demand, and supplier relationship management in the context of working capital management. Findings highlight the necessity of effective working capital management in maintaining financial stability, optimizing shareholder wealth, and ensuring long-term business viability in the retail sector. Strategies for enhancing profitability, such as improving supplier relationships and adapting to market demands, are identified. This research contributes to understanding the economic impact of the retail sector and the intricacies of working capital management. It offers insights for policymakers, retail managers, and academics, emphasizing the need for supportive retail industry measures and effective financial management practices. The study fills a gap in literature and sets a foundation for future research in this critical area of economic studies and retail management.

Optimizing Customer Relationships: A Case Study of CRM Practices at Puma Outlet in Ahmedabad city of Gujarat

Effective client Relationship Management (CRM) techniques are essential in the current competitive retail environment to maintain client loyalty and stimulate corporate expansion. This study aims to investigate and assess customer relationship management (CRM) techniques used in Puma shops. It seeks to provide insights into the impact of these tactics on customer relationships and the overall success of the organisation. The study uses a qualitative methodology, conducting in-depth interviews with branch managers in various geographical areas and market conditions. The findings indicate that common customer relationship management (CRM) tactics include the use of technology to handle data, personalised marketing efforts, and the implementation of loyalty programmes. The positives that have been identified include the efficient utilisation of customer data and the proactive interaction with customers. On the other hand, the limitations are related to the integration of CRM practices across all points of contact and the maintenance of data quality.This study makes theoretical contributions by connecting CRM theories with actual implementations, emphasising the changing role of technology and human interaction in enhancing CRM effectiveness. This study enhances the current CRM literature by offering in-depth understanding of a particular retail environment, opening up opportunities for further investigation into upcoming technologies and CRM tactics across other retail sectors.Ultimately, the results emphasise the crucial significance of CRM methods in cultivating client connections and promoting retail achievements in the digital age. Retail managers may use these observations to continually enhance their CRM strategies, while researchers are urged to explore more into the ever-changing environment of CRM to further enhance retail efficiency and consumer involvement.

HYPER ENGINEERING COMMUNICATION SKILLS WITH PECHA KUCHA TECHNIQUE FOR HIGHLY QUALITY GRADUATE ATTRIBUTES

Stakeholders in business programs, particularly marketing programs, emphasize the importance of communication skills. Graduates should develop communication skills so that they can be productive employees at work and communicate their ideas effectively to clients. Despite of the significance of being able to communicate effectively for professional graduates, there is little reference to the development of these skills in the current graduate attributes of many universities. This study was carried out to examine students experience on Pecha Kucha technique used for presenting their assignment presentation. A total of 52 students from Retail Management class have participated in the survey distributed from April to May 2022. Majority of students strongly agree that Pecha Kucha technique helped them to improve presentation skills, increase understanding on the subject also encourage more cooperative learning. It was discovered that critical thinking skills were enhanced among students while they preparing for the presentation.

Enhancing Customer Relationships: A Case Study of CRM Practices at City Square Mart in Ahmedabad city of Gujarat State

This study paper provides an in-depth examination of customer relationship management (CRM) operations conducted at City Square Mart, a well-known retail business specializing in supermarket trends. This research seeks to provide insights that will improve the development and implementation of CRM strategies in the retail industry by conducting interviews with store managers and analyzing their CRM methods. This study analyzes key elements of consumer engagement channels, such as in-store experiences and online platforms, to understand how City Square Mart effectively combines these channels to provide a seamless and cohesive customer experience. This research also examines consumer feedback methods, loyalty programs, complaint management processes, and initiatives aimed at personalization and customization of goods. The results of this research provide important insights for retail managers who want to improve their CRM strategies and for academics who want to increase their understanding of customer relationship management in the retail industry. This research aims to improve customer interactions and drive company success in the changing retail market by analyzing the unique CRM tactics implemented by City Square Mart

Predicting E-commerce customer satisfaction: Traditional machine learning vs. deep learning approaches

The rapid growth of e-commerce has increased the need for retailers to understand and predict customer satisfaction to support data-driven managerial decisions. This study analyzes online consumer behavior through a comparative machine learning modeling approach to forecast future customer satisfaction based on review ratings. Using a large dataset of over 100 k online orders from a major retailer, traditional machine learning models including random forest and support vector machines are benchmarked against deep learning techniques like multi-layer perceptrons. The predictive models are assessed for their ability to accurately predict customer satisfaction scores for the next orders based on key e-commerce features including delivery time, order value, and location. The findings demonstrate that the random forest model can predict future satisfaction with 92% accuracy, outperforming deep learning. The analysis further identifies core drivers of satisfaction such as delivery time and order accuracy. These insights enable retail managers to make targeted improvements, like optimizing logistics, to increase customer loyalty and revenue. This study provides a framework for leveraging predictive analytics and machine learning to unlock data-driven insights into online consumer behavior and satisfaction for superior retail decision-making. The focus on generalizable insights across a major retailer enhances the practical applicability of the machine learning approach for the retail sector.

Managing the co-creation of accessible and inclusive family recreation retail encounters: A critical incident analysis

Entertainment and recreation are pull factors for retail shopping malls and supercentres. For families in particular, recreation is a relevant part of their retail visits. However, families with children with disabilities (FCwD) continue to face access challenges in retail service environments. In this paper, we empirically explore how a value co-creation process undertaken with FCwD can enhance their perception of an accessible and inclusive family recreation retail visit. Our findings are based on a collaborative research project conducted in 2019 with a major shopping mall in the city of Barcelona, Spain. The methodology consisted of focus groups with stakeholders, ethnographic techniques and interviews with 20 FCwD using a constant comparative technique. The research design included two studies: Study 1, on the design of accessible and inclusive recreation retail encounters for FCwD, and Study 2, on the design of accessible and inclusive recreation retail encounters with FCwD. Using critical incident techniques (CIT), we found that the families perceived the recreation retail encounters in Study 2 to be more inclusive and accessible. From this research, we provide retail managers with recommendations for the successful design of inclusive family recreation retail opportunities in shopping malls.

What makes neighbourhood-level commercial centres attractive for neighbourhood residents?

ABSTRACT Neighbourhood commercial centres (NCC) are dynamic hubs that provide essential goods, promote community bonds and drive economic growth. Despite numerous studies on shopping behaviour, there remains a notable gap in understanding how transportation and shopping centre-related factors collectively shape the attractiveness of the NCCs, especially in developing countries like India. This research aims to understand why some NCCs outperform others in terms of attractiveness. This study proposes the neighbourhood commercial centre attractiveness index (NCCAI), which is developed by collecting 455 samples from 13 NCCs with the help of a primary survey to understand how different factors influence the attractiveness of NCCs in the Indian planned city context. The study used principal component analysis (PCA) and identified five major components that significantly contribute to NCC’s attractiveness. Further, the weightage of the components was determined through two distinct approaches: one based on PCA results and the other utilising the analytic hierarchy process (AHP) with expert opinion data. Finally, the more reliable weights from these two methodologies were selected using analysis of covariance (ANCOVA). The NCCAI can help urban planners, store owners and retail managers, providing data-driven insights to enhance overall NCC attractiveness. The decomposable nature of NCCAI allows for component score breakdown, enabling planners and policymakers to allocate resources strategically.

Evaluating carbon cap and trade policy effects on a multi-period bi-objective closed-loop supply chain in retail management under mixed uncertainty: Towards greener horizons

In response to the growing imperative of addressing environmental concerns and aligning with governmental regulations in supply chain management, this study navigates the optimization landscape of closed-loop supply chains through the lens of carbon cap and trade policy. The optimization model aims to account for the impact of consumer demands, distribution networks, and retail operations on the overall closed-loop supply chain dynamics. The innovative approach introduces an optimization model designed to grapple with the challenges posed by imprecise information within an intuitionistic type-2 fuzzy framework. The bi-objective mixed-integer model integrates pivotal objectives, including carbon emissions reduction, total cost minimization, and trade policy compliance. For a nuanced comprehension of the proposed model, we present three numerical examples, offering clarity on its complexities. Following this, a sensitivity analysis visually depicts the impact of fluctuations in demand and capacity on the defined objective functions. Furthermore, these conclusions unveil promising avenues for future research and exploration within the ambit of this study.

Testing the relationship of the digital supply chain in implementing the retail management strategy

تهدف الدراسة الى اختبار سلسلة التجهيز الرقمية وعلاقته في تنفيذ استراتيجية إدارة التجزئة وذلك عن طريق استطلاع مجتمع العينة من مالكين او أصحاب متاجر التجزئة والجملة في النجف الاشرف ، وجاءت الدراسة لتسد الفجوة المعرفية المتمثلة بندرة الدراسات العربية او الأجنبية على حد علم الباحثة التي تناولت العلاقة بين متغيرات الدراسة الحالية في انموذج فرضي واحد ، واستهدفت أسلوب الحصر الشامل على مجتمع الدراسة المتمثلة بمتاجر التجزئة والجملة اذ تم توزيع (95) استبانة وبعد فرز البيانات وتدقيقها تبين أن الاستبانات الصالحة للتحليل هي (85) استبانة من أصل (95) استبانة مسترجعة, وتم تحليلها وفقاً لأسلوب نمذجة المعادلات الهيكلية / طريقة المربعات الصغرى ، وتوصلت الدراسة الى مجموعة من النتائج وأهمها وجود علاقة تأثير وارتباط بين سلسلة التجهيز الرقمي وتنفيذ استراتيجية إدارة التجزئة .

Connecting the dots between brand equity and brand loyalty for retailers: The mediating roles of brand attitudes and word-of-mouth communication

Managing and developing brand equity is of crucial interest to retailers. To provide a better understanding of retailer brand equity, we introduce a specific nomological network that brings together operational retailer brand equity dimensions and marketing performance outcomes. More specifically, we hypothesize that consumer attitudes toward the retailer and word-of-mouth communication individually and sequentially mediate the relationship between retailer brand equity and consumer loyalty toward the retailer. Partial least squares path modeling (PLS) was used to test the proposed model with 335 US consumers from the home improvement retail sector. A systematic validation procedure with explanatory (i.e., in-sample) and predictive (i.e., out-of-sample) power assessments and robustness tests such as the confirmatory tetrad analysis and model comparison confirms these specific relationships. The results show that the refined model allows retail managers to link brand equity dimensions to marketing performance more accurately and to predict customer loyalty more reliably.

Retail management policy through firefly algorithm under uncertainty using Dempster-Shafer theory for production firm

With the emergence of challenges in production and inventory fields, there is a need for innovative management concepts. Due to the sensitivity and popularity of smart electronic gadgets, inventory management is highly likely to be damaged in production and holding processes. This study presents a model in uncertain conditions to investigate real-life situations and apply the results. In this model, due to the product’s vulnerability, the damage rate is considered one of the most important parameters. In this research, Dempster-Shafer’s theory is applied to deal with the uncertainty condition of a stochastic damaging rate. As traditional methods cannot search for parametric continuous space, genetic algorithms, and firefly algorithms are used to solve them. Finally, by performing sensitivity analysis and evaluation of algorithms, it is shown that the genetic algorithm uses less amount of time than the firefly algorithm. On the other hand, the total cost of a system with a genetic algorithm is greater than the firefly algorithm. Although the answers obtained from the two algorithms used are almost equal, the firefly algorithm provides a better answer for the optimal objective function. In the genetic algorithm, the optimal values are found to be $0.68756 for the damaging rate and $1896.22 for the total cost. Conversely, the firefly algorithm yields optimal values of $0.68395 for the damaging rate and $1895.1576 for the total cost. These results highlight the efficacy of both algorithms in optimizing the specified parameters, providing valuable insights for inventory management systems.